Gravitational Search Algorithm Based on Random Black Hole and Adaptive Strategy

An improved gravitational search algorithm based on random black hole strategy and gravitational constant adaptive strategy is proposed to solve the problem that the gravitational search algorithm is too random, the global search ability is poor, and the local optimum is easy to fall into. The proportion coefficient n is introduced from the adaptive adjustment of gravity constant, which makes the algorithm increase the search power in the initial stage, and effectively avoid the algorithm falling into local optimum. As for random black hole theory, the phenomenon that particles are easily captured by black hole near the black hole. This was considered for the algorithm. The particles in the radius of the black hole would be captured by the black hole, but there would be a certain probability to escape, which not only improves the local search ability, but also improves the global search ability and the convergence speed. Compared with the cable algorithm, the improved gravitational search algorithm has faster convergence and better optimization performance.